PoliBERT Sentiment Analysis

Political sentiment analysis using PoliBERTweet - a RoBERTa model pre-trained on 83M political tweets. Analyzes support, opposition, and stance toward politi...

This skill is coherent for political sentiment analysis but review these points before installing: 1) Installing will pull heavy ML dependencies and the PoliBERT model (~500MB) — expect large downloads and GPU/CPU resource usage. 2) requirements.txt pins versions and includes packages (pandas, scikit-learn) that the main script doesn't appear to need; consider installing only the packages you require to reduce footprint. 3) The code intends to fetch Reddit in read-only mode without credentials; PRAW usage here is uncredentialed but verify behavior in your environment (and rate limits). 4) test_sample.sh uses an absolute user path and activates a venv at that path — do not run it without adjusting the path to your environment. 5) The model comes from the HuggingFace handle in the SKILL.md; if provenance matters, verify the model owner and license on HuggingFace before use. 6) As with any political-analysis tool, results can be biased; validate outputs and consider ethical/privacy implications when analyzing user data or large social datasets.

Type: OpenClaw Skill Name: polibert-sentiment Version: 1.0.0 The polibert-sentiment skill is a legitimate tool for political sentiment analysis using the PoliBERTweet model from HuggingFace and Reddit data via the PRAW library. The code in polibert_sentiment.py and scrape_polymarket.py performs its stated functions without any evidence of data exfiltration, malicious execution, or prompt injection. While test_sample.sh contains a hardcoded local file path, this appears to be a remnant of development rather than a malicious indicator.